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Journal articles on the topic 'Proxy Caching'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Cáceres, Ramón, Fred Douglis, Anja Feldmann, Gideon Glass, and Michael Rabinovich. "Web proxy caching." ACM SIGMETRICS Performance Evaluation Review 26, no. 3 (December 1998): 11–15. http://dx.doi.org/10.1145/306225.306230.

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2

Wang, James Z., Zhidian Du, and Pradip K. Srimani. "Cooperative Proxy Caching for Wireless Base Stations." Mobile Information Systems 3, no. 1 (2007): 1–18. http://dx.doi.org/10.1155/2007/371572.

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This paper proposes a mobile cache model to facilitate the cooperative proxy caching in wireless base stations. This mobile cache model uses a network cache line to record the caching state information about a web document for effective data search and cache space management. Based on the proposed mobile cache model, a P2P cooperative proxy caching scheme is proposed to use a self-configured and self-managed virtual proxy graph (VPG), independent of the underlying wireless network structure and adaptive to the network and geographic environment changes, to achieve efficient data search, data cache and date replication. Based on demand, the aggregate effect of data caching, searching and replicating actions by individual proxy servers automatically migrates the cached web documents closer to the interested clients. In addition, a cache line migration (CLM) strategy is proposed to flow and replicate the heads of network cache lines of web documents associated with a moving mobile host to the new base station during the mobile host handoff. These replicated cache line heads provide direct links to the cached web documents accessed by the moving mobile hosts in the previous base station, thus improving the mobile web caching performance. Performance studies have shown that the proposed P2P cooperative proxy caching schemes significantly outperform existing caching schemes.

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3

Pratama, Gunadi, Jajang Mulyana, and Wawan Kusdiawan. "MEMBANGUN PROXY SERVER WEB CACHE DENGAN ANALISIS PERBANDINGAN CACHE REPLACEMENT PADA SQUID PROXY." Syntax : Jurnal Informatika 9, no. 2 (October 25, 2020): 98–109. http://dx.doi.org/10.35706/syji.v9i2.3823.

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Pada sebuah jaringan komputer terdapat Proxy server yang memiliki fungsi salah satunya caching. Mekanisme caching pada proxy server adalah menyimpan objek-objek yang merupakan hasil permintaan komputer client dari internet dan memberikan layanan jika client akan mengaksesnya kembali tanpa meminta sepenuhnya ke internet. Mengingat bahwa cache memory merupakan penyimpanan yang tetap maka dapat memungkinkan terjadinya cache memory penuh, untuk mengoptimalisasi kinerja cache memory terdapat metode cache replacement pada proxy server. Cache replacement pada proxy server merupakan metode penghapusan objek pada cache memory untuk digantikan dengan objek baru yang bertujuan agar cache memory tidak penuh. Maka dari itu penulis akan membangun sebuah proxy server web cache serta menganalisis algoritme Least recently used dan Greedy dual size frequently sebagai aturan cache replacement pada squid proxy dengan menggunakan metode pengembangan Netwok Development Live Cycle (NDLC) Cisco PPDIOO. Kata kunci: Proxy server, Caching, Cache Replacement, LRU, GDSF, Cisco PPDIOO.

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4

Cano, J. C., A. Pont, J. Sahuquillo, and J. A. Gil. "The differences between distributed shared memory caching and proxy caching." IEEE Concurrency 8, no. 3 (July 2000): 45–47. http://dx.doi.org/10.1109/4434.865892.

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5

Liu, Wei. "Proxy Caching for Interactive Streaming Media." Journal of Computer Research and Development 43, no. 4 (2006): 594. http://dx.doi.org/10.1360/crad20060404.

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6

Cheng, Kai, and Yahiko Kambayashi. "Enhanced Proxy Caching with Content Management." Knowledge and Information Systems 4, no. 2 (April 2002): 202–18. http://dx.doi.org/10.1007/s101150200004.

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7

Yasin. "WINDOWS WEB PROXY CACHING SIMULATION: A TOOL FOR SIMULATING WEB PROXY CACHING UNDER WINDOWS OPERATING SYSTEMS." Journal of Computer Science 10, no. 8 (August 1, 2014): 1380–88. http://dx.doi.org/10.3844/jcssp.2014.1380.1388.

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8

Sathiyamoorthi, V. "A Novel Cache Replacement Policy for Web Proxy Caching System Using Web Usage Mining." International Journal of Information Technology and Web Engineering 11, no. 2 (April 2016): 1–13. http://dx.doi.org/10.4018/ijitwe.2016040101.

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Network congestion remains one of the main barriers to the continuing success of the internet and Web based services. In this background, proxy caching is one of the most successful solutions for civilizing the performance of Web since it reduce network traffic, Web server load and improves user perceived response time. Here, the most popular Web objects that are likely to be revisited in the near future are stored in the proxy server thereby it improves the Web response time and saves network bandwidth. The main component of Web caching is it cache replacement policy. It plays a key role in replacing existing objects when there is no room for new one especially when cache is full. Moreover, the conventional replacement policies are used in Web caching environments which provide poor network performance. These policies are suitable for memory caching since it involves fixed sized objects. But, Web caching which involves objects of varying size and hence there is a need for an efficient policy that works better in Web cache environment. Moreover, most of the existing Web caching policies have considered few factors and ignored the factors that have impact on the efficiency of Web proxy caching. Hence, it is decided to propose a novel policy for Web cache environment. The proposed policy includes size, cost, frequency, ageing, time of entry into the cache and popularity of Web objects in cache removal policy. It uses the Web usage mining as a technique to improve Web caching policy. Also, empirical analyses shows that proposed policy performs better than existing policies in terms of various performance metrics such as hit rate and byte hit rate.

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9

Yang, Jiong, Wei Wang, and Richard Muntz. "Collaborative Web caching based on proxy affinities." ACM SIGMETRICS Performance Evaluation Review 28, no. 1 (June 2000): 78–89. http://dx.doi.org/10.1145/345063.339360.

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10

Wooster, Roland P., and Marc Abrams. "Proxy caching that estimates page load delays." Computer Networks and ISDN Systems 29, no. 8-13 (September 1997): 977–86. http://dx.doi.org/10.1016/s0169-7552(97)00041-x.

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11

Dykes, S. G., and K. A. Robbins. "Limitations and benefits of cooperative proxy caching." IEEE Journal on Selected Areas in Communications 20, no. 7 (September 2002): 1290–304. http://dx.doi.org/10.1109/jsac.2002.801750.

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12

Peng, Xiaoyu, Jiahao Liang, Baili Zhang, and Tong Liu. "PCR: caching replacement algorithm in proxy server." International Journal of Computational Science and Engineering 21, no. 4 (2019): 495. http://dx.doi.org/10.1504/ijcse.2019.10028616.

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13

Liu, Tong, Xiaoyu Peng, Jiahao Liang, and Baili Zhang. "PCR: caching replacement algorithm in proxy server." International Journal of Computational Science and Engineering 21, no. 4 (2020): 495. http://dx.doi.org/10.1504/ijcse.2020.106862.

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14

Wu, K. L., P. S. Yu, and J. L. Wolf. "Segmentation of Multimedia Streams for Proxy Caching." IEEE Transactions on Multimedia 6, no. 5 (October 2004): 770–80. http://dx.doi.org/10.1109/tmm.2004.834870.

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15

Wang, James Z., and Philip S. Yu. "Fragmental Proxy Caching for Streaming Multimedia Objects." IEEE Transactions on Multimedia 9, no. 1 (January 2007): 147–56. http://dx.doi.org/10.1109/tmm.2006.886379.

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16

Omara, Fatma. "A LOW LATENCY PROXY PREFETCHING CACHING ALGORITHM." International Conference on Aerospace Sciences and Aviation Technology 10, ASAT CONFERENCE (May 1, 2003): 1–20. http://dx.doi.org/10.21608/asat.2013.24708.

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17

Dykstra, Josiah. "Using apache as a caching proxy server." XRDS: Crossroads, The ACM Magazine for Students 7, no. 5 (July 5, 2001): 5. http://dx.doi.org/10.1145/969637.969642.

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18

Hao, Wei, Jicheng Fu, Jiang He, I.-Ling Yen, Farokh Bastani, and Ing-Ray Chen. "Extending Proxy Caching Capability: Issues and Performance." World Wide Web 9, no. 3 (June 8, 2006): 253–75. http://dx.doi.org/10.1007/s11280-006-8556-0.

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19

Tian, Zhuo, and Bai Cheng Li. "Segment-Based Proxy Caching for Streaming Media Delivery." Advanced Materials Research 1049-1050 (October 2014): 1824–27. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1824.

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At present the majority of streaming media files is large and it requires a lot of network bandwidth and disk bandwidth. We propose an adaptive segment-based method, the cache replacement method and the multi technologies combined optimized transmission policy. Simulation results indicate that they are highly efficient methods for use of caching proxy server resources, reducing the startup latency and save of bandwidth of backbone network.

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20

Zeng, D., F. Y. Wang, and M. Liu. "Efficient Web Content Delivery Using Proxy Caching Techniques." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 34, no. 3 (August 2004): 270–80. http://dx.doi.org/10.1109/tsmcc.2004.829261.

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21

Nishikawa, Norifumi, Takafumi Hosokawa, Yasuhide Mori, Kenichi Yoshida, and Hiroshi Tsuji. "Memory-based architecture for distributed WWW caching proxy." Computer Networks and ISDN Systems 30, no. 1-7 (April 1998): 205–14. http://dx.doi.org/10.1016/s0169-7552(98)00117-2.

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22

Kangasharju, Jussi, Young Gap Kwon, and Antonio Ortega. "Design and implementation of a soft caching proxy." Computer Networks and ISDN Systems 30, no. 22-23 (November 1998): 2113–21. http://dx.doi.org/10.1016/s0169-7552(98)00254-2.

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23

Zhourong Miao and A. Ortega. "Scalable proxy caching of video under storage constraints." IEEE Journal on Selected Areas in Communications 20, no. 7 (September 2002): 1315–27. http://dx.doi.org/10.1109/jsac.2002.802061.

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24

Mahanti, A., C. Williamson, and D. Eager. "Traffic analysis of a Web proxy caching hierarchy." IEEE Network 14, no. 3 (2000): 16–23. http://dx.doi.org/10.1109/65.844496.

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25

Kharat, M. U., and Narendra S. Chaudhar . "Efficient Caching Proxy Server Parameters: An Integrated Approach." Information Technology Journal 5, no. 2 (February 15, 2006): 300–304. http://dx.doi.org/10.3923/itj.2006.300.304.

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26

Jiangchuan Liu and Jianliang Xu. "Proxy caching for media streaming over the Internet." IEEE Communications Magazine 42, no. 8 (August 2004): 88–94. http://dx.doi.org/10.1109/mcom.2004.1321397.

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27

TAGASHIRA, S. "Proxy-Based Index Caching for Content-Addressable Networks." IEICE Transactions on Information and Systems E89-D, no. 2 (February 1, 2006): 555–62. http://dx.doi.org/10.1093/ietisy/e89-d.2.555.

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28

Xu, Ke, Ming Zhang, Jiangchuan Liu, Zhijing Qin, and Mingjiang Ye. "Proxy caching for peer-to-peer live streaming." Computer Networks 54, no. 7 (May 2010): 1229–41. http://dx.doi.org/10.1016/j.comnet.2009.11.013.

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29

Kumar, Chetan, and Sean Marston. "Accelerating the Internet in the presence of Big Data: Reducing user delays by leveraging historical user request patterns for web caching." Journal of Information Systems and Technology Management 16 (March 30, 2019): 1–10. http://dx.doi.org/10.4301/s1807-1775201916006.

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Approximately 4 billion people have access to the Internet, additionally 23 billion devices are connected as of 2018. This has allowed for a substantial growth in data collection which has allowed for Big Data to flourish. The continued increase in user, devices, and Big Data usage has created a significant intensification in Internet traffic. This in turn has the potential to increase user delays when accessing data on the Internet. There are a number of ways to help reduce user latency, web caching is able to reduce web user delays in addition to reducing network traffic and the load on web servers. In this study we propose a proxy level web caching mechanism leveraging historical web patterns to help reduce user latency and accelerate the Internet. In addition we survey the state of the art of other caching approaches. Our investigation shows that using historical patterns as part of a proxy caching mechanisms in large scale networks can significantly shorten the latency for users in this era of Big Data

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30

WANG, JAMES Z., and VIPUL BHULAWALA. "DESIGN AND IMPLEMENTATION OF A P2P COOPERATIVE PROXY CACHE SYSTEM." Journal of Interconnection Networks 08, no. 02 (June 2007): 147–62. http://dx.doi.org/10.1142/s0219265907001953.

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In this paper, we design and implement a P2P cooperative proxy caching system based on a novel P2P cooperative proxy caching scheme. To effectively locate the cached web documents, a TTL-based routing protocol is proposed to manage the query and response messages in the P2P cooperative proxy cache system. Furthermore, we design a predict query-route algorithm to improve the TTL-based routing protocol by adding extra information in the query message packets. To select a suitable cache replacement algorithm for the P2P cooperative proxy cache system, three different cache replacement algorithms, LRU, LFU and SIZE, are evaluated using web trace based performance studies on the implemented P2P cooperative proxy cache system. The experimental results show that LRU is an overall better cache replacement algorithm for the P2P proxy cache system although SIZE based cache replacement approach produces slightly better cache hit ratio when cache size is very small. The performance studies also demonstrate that the proposed message routing protocols significantly improve the performance of the P2P cooperative proxy cache system, in terms of cache hit ratio, byte hit ratio, user request latency, and the number of query messages generated in the proxy cache system, compared to the flooding based message routing protocol.

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31

Dykstra, Dave, Brian Bockelman, Jakob Blomer, and Laurence Field. "The Open High Throughput Computing Content Delivery Network." EPJ Web of Conferences 214 (2019): 04023. http://dx.doi.org/10.1051/epjconf/201921404023.

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LHC experiments make extensive use of web proxy caches, especially for software distribution via the CernVM File System and for conditions data via the Frontier Distributed Database Caching system. Since many jobs read the same data, cache hit rates are high and hence most of the traffic flows efficiently over Local Area Networks. However, it is not always possible to have local web caches, particularly for opportunistic cases where experiments have little control over site services. The Open High Throughput Computing (HTC) Content Delivery Network (CDN), openhtc.io, aims to address this by using web proxy caches from a commercial CDN provider. Cloudflare provides a simple interface for registering DNS aliases of any web server and does reverse proxy web caching on those aliases. The openhtc.io domain is hosted on Cloudflare's free tier CDN which has no bandwidth limit and makes use of data centers throughout the world, so the average performance for clients is much improved compared to reading from CERN or a Tier 1. The load on WLCG servers is also significantly reduced. WLCG Web Proxy Auto Discovery is used to select local web caches when they are available and otherwise select openhtc.io caching. This paper describes the Open HTC CDN in detail and provides initial results from its use for LHC@Home and USCMS opportunistic computing.

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32

Songqing Chen, Haining Wang, Xiaodong Zhang, Bo Shen, and Susie Wee. "Segment-Based Proxy Caching for Internet Streaming Media Delivery." IEEE Multimedia 12, no. 3 (July 2005): 59–67. http://dx.doi.org/10.1109/mmul.2005.56.

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33

Verscheure, Olivier, Chitra Venkatramani, Pascal Frossard, and Lisa Amini. "Joint server scheduling and proxy caching for video delivery." Computer Communications 25, no. 4 (March 2002): 413–23. http://dx.doi.org/10.1016/s0140-3664(01)00413-3.

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34

Raunak, Mohammad S., Prashant Shenoy, Pawan Goyal, and Krithi Ramamritham. "Implications of proxy caching for provisioning networks and servers." ACM SIGMETRICS Performance Evaluation Review 28, no. 1 (June 2000): 66–77. http://dx.doi.org/10.1145/345063.339357.

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35

Benadit, P. Julian, F. Sagayaraj Francis, and U. Muruganantham. "Enhancement of web proxy caching using discriminative multinomial Na." International Journal of Information and Communication Technology 11, no. 3 (2017): 369. http://dx.doi.org/10.1504/ijict.2017.086831.

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36

Muruganantham, U., P. Julian Benadit, and F. Sagayaraj Francis. "Enhancement of web proxy caching using discriminative multinomial Na." International Journal of Information and Communication Technology 11, no. 3 (2017): 369. http://dx.doi.org/10.1504/ijict.2017.10007929.

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37

Ali, Waleed, Siti Mariyam Shamsuddin, and Abdul Samad Ismail. "Intelligent Naïve Bayes-based approaches for Web proxy caching." Knowledge-Based Systems 31 (July 2012): 162–75. http://dx.doi.org/10.1016/j.knosys.2012.02.015.

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38

Raunak, M., P. Shenoy, P. Goyal, K. Ramamritham, and P. Kulkarni. "Implications of proxy caching for provisioning networks and servers." IEEE Journal on Selected Areas in Communications 20, no. 7 (September 2002): 1276–89. http://dx.doi.org/10.1109/jsac.2002.801751.

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39

Ortiz, J. P. G., V. G. Ruiz, M. F. Lopez, and I. Garcia. "Interactive Transmission of JPEG2000 Images Using Web Proxy Caching." IEEE Transactions on Multimedia 10, no. 4 (June 2008): 629–36. http://dx.doi.org/10.1109/tmm.2008.921738.

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40

Sathiyamoorthi V., Jayapandian N., Gnana Prakasi O. S., Kanmani P., Revathi Vaithiyanathan, and Prasanth Rao A. "Analyzing and Optimizing the Usability of Website Access." International Journal of Web Portals 12, no. 2 (July 2020): 22–40. http://dx.doi.org/10.4018/ijwp.2020070102.

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The world wide web (WWW) plays a significant role in information sharing and distribution. In web-based information access, the speed of information retrieval plays a critical role in shaping the web usability and determining the user satisfaction in accessing webpages. To deal with this problem, web caching is used. The problem with the present web caching system is that it is very hard to recognize webpages that are to be accessed and then to be cached. This is forced by the fact that there are broad categories of users and each one having their own preferences. Hence, it is decided to propose a novel approach for web access pattern generation by analyzing the web log file present in the proxy server. Further, it tries to propose a novel hybrid policy called popularity-aware modified least frequently used (PMLFU) that best suits for the current proxy-based web caching environment. It combines features such as frequency, recency, popularity, and user page count in decision-making policy. The performance of the proposed system is observed using real-time datasets, empirically using IRCACHE datasets.

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41

Al-Dailami, Abdulrahman, Chang Ruan, Zhihong Bao, and Tao Zhang. "QoS3: Secure Caching in HTTPS Based on Fine-Grained Trust Delegation." Security and Communication Networks 2019 (December 28, 2019): 1–16. http://dx.doi.org/10.1155/2019/3107543.

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With the ever-increasing concern in network security and privacy, a major portion of Internet traffic is encrypted now. Recent research shows that more than 70% of Internet content is transmitted using HyperText Transfer Protocol Secure (HTTPS). However, HTTPS encryption eliminates the advantages of many intermediate services like the caching proxy, which can significantly degrade the performance of web content delivery. We argue that these restrictions lead to the need for other mechanisms to access sites quickly and safely. In this paper, we introduce QoS3, which is a protocol that can overcome such limitations by allowing clients to explicitly and securely re-introduce in-network caching proxies using fine-grained trust delegation without compromising the integrity of the HTTPS content and modifying the format of Transport Layer Security (TLS). In QoS3, we classify web page contents into two types: (1) public contents that are common for all users, which can be stored in the caching proxies, and (2) private contents that are specific for each user. Correspondingly, QoS3 establishes two separate TLS connections between the client and the web server for them. Specifically, for private contents, QoS3 just leverages the original HTTPS protocol to deliver them, without involving any middlebox. For public contents, QoS3 allows clients to delegate trust to specific caching proxy along the path, thereby allowing the clients to use the cached contents in the caching proxy via a delegated HTTPS connection. Meanwhile, to prevent Man-in-the-Middle (MitM) attacks on public contents, QoS3 validates the public contents by employing Document object Model (DoM) object-level checksums, which are delivered through the original HTTPS connection. We implement a prototype of QoS3 and evaluate its performance in our testbed. Experimental results show that QoS3 provides acceleration on page load time ranging between 30% and 64% over traditional HTTPS with negligible overhead. Moreover, QoS3 is deployable since it requires just minor software modifications to the server, client, and the middlebox.

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42

Ghofir, Abdul, and Rikip Ginanjar. "Distributed Cache with Utilizing Squid Proxy Server and LRU Algorithm." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 2 (August 1, 2017): 474. http://dx.doi.org/10.11591/ijeecs.v7.i2.pp474-482.

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<p>In relation to the dissemination of information, the Internet is one of the fastest media to do so. The internet’s presence is growing very swiftly and rapidly, so it has become recognized by people from all walks of life. For that, the people need the appropriate way to maintain effectiveness in the use of the Internet. The following paper describes a study of the distribution of the cache, which is performed by the squid proxy server by creating a storage network design on Linux. Cache documents that are stored in the proxy server will be distributed to another over a network storage server. The process of caching on the proxy server is using the Least Recently Used (LRU) Algorithm. This research was carried out by developing the existing method of caching server process, then it is to be added a unit as a backup storage device for the data that must be erased because of the replacement policy applied to the squid proxy server. This study is looking at how the hit ratio and byte hit ratio after adding the storage server compared to not having a storage server. At the end of this research, it is concluded that the distributed cache processes a hit ratio and byte hit ratio higher than the cache on the current proxy server.</p>

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43

Hong, Hyeon-Ok, Eun-Ji Im, and Gi-Dong Jeong. "Playback Quantity-based Proxy Caching Scheme for Continuous Media Data." KIPS Transactions:PartB 9B, no. 3 (June 1, 2002): 303–10. http://dx.doi.org/10.3745/kipstb.2002.9b.3.303.

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44

Wolman, Alec, M. Voelker, Nitin Sharma, Neal Cardwell, Anna Karlin, and Henry M. Levy. "On the scale and performance of cooperative Web proxy caching." ACM SIGOPS Operating Systems Review 33, no. 5 (December 12, 1999): 16–31. http://dx.doi.org/10.1145/319344.319153.

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45

Wolman, Alec, Geoffrey M. Voelker, Nitin Sharma, Neal Cardwell, Anna Karlin, and Henry M. Levy. "On the scale and performance of cooperative Web proxy caching." ACM SIGOPS Operating Systems Review 34, no. 2 (April 2000): 11–12. http://dx.doi.org/10.1145/346152.346166.

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46

Gruber, Stephane, Jennifer Rexford, and Andrea Basso. "Protocol considerations for a prefix-caching proxy for multimedia streams." Computer Networks 33, no. 1-6 (June 2000): 657–68. http://dx.doi.org/10.1016/s1389-1286(00)00058-x.

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47

Ma, W., and D. H. C. Du. "Design a Progressive Video Caching Policy for Video Proxy Servers." IEEE Transactions on Multimedia 6, no. 4 (August 2004): 599–610. http://dx.doi.org/10.1109/tmm.2004.830819.

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48

Wauters, Tim, Wim Van De Meerssche, Peter Backx, Filip De Turck, Bart Dhoedt, Piet Demeester, Tom Van Caenegem, and Erwin Six. "Proxy caching algorithms and implementation for time-shifted TV services." European Transactions on Telecommunications 19, no. 2 (2008): 111–22. http://dx.doi.org/10.1002/ett.1181.

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49

Ma, Wei-Hsiu, and David H. C. Du. "Frame Selection for Dynamic Caching Adjustment in Video Proxy Servers." Multimedia Tools and Applications 22, no. 1 (January 2004): 53–73. http://dx.doi.org/10.1023/b:mtap.0000008659.52373.fc.

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50

Fang Yu, Qian Zhang, Wenwu Zhu, and Ya-Qin Zhang. "QoS-adaptive proxy caching for multimedia streaming over the internet." IEEE Transactions on Circuits and Systems for Video Technology 13, no. 3 (March 2003): 257–69. http://dx.doi.org/10.1109/tcsvt.2003.809829.

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